Citations

This cross-sectional study evaluates the performance of the US Food and Drug Administration–cleared phosphorylated tau 217 (p-tau217) to β-amyloid 42 ratio cut points used to detect amyloid pathology associated with Alzheimer disease.

Abstract INTRODUCTION Remote neuropsychological testing can monitor brain health in individuals with or at risk of Alzheimer's disease (AD). We evaluated acceptability and validity of the Cogstate Brief Battery (CBB) for remote administration. METHODS Non‐demented adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) completed the CBB in‐clinic under supervision, then remotely every six months, with annual in‐clinic reassessments. Groups included cognitively unimpaired (CU) adults with normal amyloid (CU Aβ−) or elevated amyloid (CU Aβ+), and individuals with mild cognitive impairment with or without amyloid (MCI Aβ+, MCI Aβ−). Performance was compared across contexts and longitudinal changes were examined. RESULTS At baseline, MCI Aβ+ participants performed worse than CU Aβ−. CBB performance was similar across contexts, with consistent group differences. Over time, MCI Aβ+ participants showed greater decline on remote CBB measures than CU Aβ− adults. DISCUSSION Remote unsupervised CBB assessments are valid, reliable, and sensitive to AD‐related cognitive impairment.

Abstract INTRODUCTION We describe the reliability of remote self‐administered digital cognitive measures completed via the Mayo Test Drive (MTD) web‐based platform. METHODS A total of 1846 participants (mean age = 70, SD = 12, range 31–101; 48% male; 96% White; 99% non‐Hispanic; 97% cognitively unimpaired) with two to four complete MTD sessions at ∼7.5‐month intervals were included. Test‐retest reliability was assessed using single‐rating, absolute‐agreement, and two‐way mixed intraclass correlation coefficients (ICCs) with 95% confidence intervals. ICCs for in‐person‐administered traditional neuropsychological measures were compared to MTD for a subset of 244 participants. Analyses also compared reliability across demographic, residential, and session context subgroups. RESULTS Reliability was good for the MTD Composite (total ICC = 0.79 [0.77, 0.80]), and moderate‐to‐good for the primary outcome variables for each MTD subtest (total ICCs 0.70–0.83 for Stricker Learning Span and Symbols). The reliability of the remote self‐administered MTD was similar to in‐person‐administered cognitive measures. DISCUSSION MTD showed moderate‐to‐good reliability, supporting its use in longitudinal monitoring.

Abstract Introduction The relationship between sleep and brain metabolism remains unclear. This study aimed to examine whether overnight sleep features, using a home sleep apnea system based on peripheral arterial tonometry, are associated with regional FDG-PET changes in older adults. Methods We analyzed cognitively unimpaired adults (≥60 years) from the Mayo Clinic Study of Aging (MCSA) cohort who were not receiving sleep apnea treatment. Participants underwent overnight sleep assessment with the WatchPAT system, followed by FDG-PET imaging the next morning. FDG-PET data were co-registered to 3T MRI and automatically segmented into 122 anatomical regions. PET signal was referenced to the pons (SUVR). We computed voxel-weighted median FDG signal across 47 bilateral cortical and subcortical regions of interest (ROIs), excluding brainstem and cerebellum. Associations between sleep architecture and sleep apnea/hypoxemia burden and regional metabolism were assessed using partial Spearman’s rank correlation, adjusting for age. Results Thirty-seven participants were included (70.3% female; median [IQR] age: 72.0 [68.0–78.0] years). Wake after sleep onset (WASO) showed widespread negative associations with FDG uptake in cortical regions (p< 0.05), particularly the ventromedial/ventrolateral (rs=–0.47 to –0.33) prefrontal cortex, lateral temporal (rs=–0.38 to –0.33), and occipital (rs=–0.47 to –0.37) cortices. Total sleep time (TST) was positively associated with medial structures (p< 0.05), including the posterior cingulate (rs=0.39), retrosplenial cortex (rs=0.48), hippocampus/parahippocampal (rs=0.34 to 0.36), calcarine cortex (ρ=0.38), thalamus (rs=0.37), and caudate (rs=0.43). Hypoxic burden was positively associated with medial occipital regions (rs=0.35 to 0.39) and AHI-4% with cuneus (rs=0.33). Regional gray matter volume did not mediate these associations. WASO correlated with Insomnia Severity Index (rs=0.43, p=0.008) and self-reported refreshing sleep (rs=0.046). Conclusion Overnight sleep macrostructure features (WASO and TST) and hypoxic burden are significantly associated with brain metabolism, potentially underlying symptoms of sleep disturbance and cognitive aging. Support (if any) Mayo Clinic Alzheimer’s Disease Research Center Development Award (P30 AG062677), R01 AG056366, U01 AG006786, R01 AG056366, R01 AG034676, R37 AG011378, R01 AG041851, R01 NS097495, R01 AG068206, P30 AG062677, R01 HL065176. CLARA project work with funding from the European Union’s HORIZON EUROPE research and innovation programme (No 101136607).

Abstract INTRODUCTION Alzheimer's disease neuropathologic change (ADNC) classification identifies not/low and intermediate/high levels of neuropathology. Our goal was to assess how frequently a positive amyloid positron emission tomography (PET) scan indicates not/low ADNC and whether this autopsy finding can occur >10 years after a positive amyloid PET. METHODS Participants with positive amyloid PET scans were categorized by levels of ADNC at autopsy, grouped by time from initial positive amyloid PET to time of death (<5 years, 5 to <10 years, or 10+ years). RESULTS Among those with a positive amyloid PET scan, the majority had intermediate/high ADNC at autopsy (234/259, 90%). In the group with 10+ years between a positive amyloid PET and death ( n = 39) not/low ADNC occurred in 3/39 (8%). DISCUSSION Not/low ADNC is uncommon among those with positive amyloid PET scans. After 10+ years, it is possible but rare for a positive amyloid PET scan to represent an indolent state of neuropathology.

Abstract Alzheimer’s disease (AD) emerges from multi-scale interactions between molecular pathology and disruptions in large-scale brain network dynamics. Understanding how these processes co-evolve and relate to disease stages is essential for advancing complex systems models of aging and AD, and for developing system-informed interventions. However, progress has been limited by a lack of large-scale longitudinal data. To address this, we examined the longitudinal relationship between subsystems of the default mode network (DMN) (posterior DMN, ventral DMN, anterior dorsal DMN) using task-free functional MRI (fMRI) and amyloid positron emission tomography (PET) imaging in a large longitudinal cohort spanning the clinico-biological spectrum of AD (n = 1,451; 2,763 time points) using mixed-effect models. We also assessed whether patterns of DMN connectivity predicted conversion to amyloid positivity, mild cognitive impairment (MCI), and dementia using Cox proportional hazards models. Our findings reveal a dynamic interplay between amyloid accumulation and connectivity within and between DMN subsystems, with both hyper- and hypoconnectivity emerging across DMN subsystems in association with increasing amyloid burden. Importantly, survival models showed that DMN connectivity patterns predicted conversion to critical stages of the disease, including not only conversion to MCI and dementia, but also conversion to amyloid positivity in otherwise clinically unimpaired individuals who were amyloid negative at baseline. These associations were independent of age, APOE4 status, sex, education, and in-scanner motion. These results support a model in which breakdowns in tightly regulated feedback loops governing DMN physiology represent a core systems-level pathophysiology of AD. Notably, this functional dyshomeostasis precedes detectable amyloidosis on imaging. Future studies should focus on the development of robust biomarkers of brain function that can be applied at the individual level, which could in turn help support the development of therapeutic approaches targeting system-level pathophysiology.

Abstract Alzheimer's disease (AD) continues to pose a major public health challenge. Since its launch in 2004, the Alzheimer's Disease Neuroimaging Initiative (ADNI) has played a pivotal role in advancing the field by providing a comprehensive, open‐access, longitudinal dataset that integrates neuroimaging, biomarker, genetic, and clinical data related to AD. We used standard literature search methods to identify ∼1830 publications from 2023 to mid‐2025 that used ADNI data or samples. This review highlights key ADNI studies with direct clinical applications. We describe how these have impacted the development and validation of plasma biomarkers, improved clinical trials, assessed AD therapies, and developed methods for diagnosis and prediction using clinical, fluid, and imaging biomarkers. These contributions are underlain by an improved understanding of biological mechanisms of disease progression in AD and highlight ADNI's central role in advancing translational research and accelerating progress toward more effective, individualized care for patients with AD.

Objective Immunohistochemically (IHC) measured transactive response DNA‐binding protein 43 (TDP‐43) inclusions are observed in Alzheimer's disease (AD) and are associated with medial temporal lobe atrophy. Accumulation of cryptic exons occurs in AD in response to TDP‐43 pathology. We aimed to assess relationships between IHC and biochemically measured insoluble TDP‐43 and cryptic exons and assess associations with hippocampal and amygdala volume loss and atrophy rates on magnetic resonance imaging (MRI). Methods Eighty‐one neuropathologically diagnosed AD cases were analyzed. For biochemistry, insoluble TDP‐43 was quantified using a Meso‐scale discovery (MSD) immunoassay. IHC‐TDP burden was quantified with digital histopathology. Cryptic RNAs were assessed via quantitative real‐time polymerase chain reaction (qRT‐PCR). Thirty‐eight cases had serial brain MRI. Hippocampal and amygdala volumes were calculated using FreeSurfer. Regression models were used to investigate associations among IHC‐TDP‐43 status/burden, MSD‐TDP status/levels, cryptic RNAs, and hippocampal and amygdala volumes and atrophy rates. Results IHC‐TDP(+) cases exhibited elevated levels of MSD‐TDP and cryptic RNAs ( KCNQ2 , STMN2 , and UNC13A ) and increased MSD‐TDP levels were associated with increased cryptic RNA levels, in the hippocampus and amygdala. IHC‐TDP(+) cases had smaller hippocampal and amygdala volumes compared to IHC‐TDP(−) cases. MSD‐TDP(+) cases had smaller hippocampal volumes and faster amygdala rates of atrophy compared with MSD‐TDP(−) cases. Higher KCNQ2 and UNC13A levels were associated with smaller amygdala volumes. Interpretation MSD‐TDP level is a reliable surrogate for IHC‐based TDP‐43 status. Both TDP‐43 and cryptic RNA levels are associated with reduced medial temporal volumes, suggesting cryptic exons may be playing a role in brain volume loss in AD. ANN NEUROL 2026;100:193–205

Abstract Different MRI image contrasts are designed to highlight various tissue properties and combining them allows extension of probabilistic segmentation beyond the commonly used “gray-white-CSF” models. This work describes a fully automated method that combines T1-weighted, T2-FLAIR, and conventional T2-weighted images to provide internal consistency across prediction of tissue segmentations including segmentation of superficial and deep gray matter, white matter hyperintensities, and MR-visible perivascular spaces. Results from 773 imaging datasets from 403 participants in the Mayo Clinic Study of Aging and Mayo Clinic Alzheimer’s Disease Research Center (ADRC) are presented.